Dynamic-Data Driven Real-Time Identification for Electric Power Systems

Power system engineers face a double challenge: to operate electric power systems within narrow stability and security margins, and to maintain high reliability. There is an acute need to better understand the dynamic nature of power systems in order to be prepared for critical situations as they arise. Innovative measurement tools, such as phasor measurement units, can capture not only the slow variation of the voltages and currents but also the underlying oscillations in a power system. Such dynamic data accessibility provides us a strong motivation and a useful tool to explore dynamic-data driven applications in power systems. To fulfill this goal, this dissertation focuses on the following three areas: Developing accurate dynamic load models and updating variable parameters based on the measurement data, applying advanced nonlinear filtering concepts and technologies to real-time identification of power system models, and addressing computational issues by implementing the balanced truncation method. By obtaining more realistic system models, together with timely updated parameters and stochastic influence consideration, we can have an accurate portrait of the ongoing phenomena in an electrical power system. Hence we can further improve state estimation, stability analysis and real-time operation.

An Approach to Manage Reconfigurations and Reduce Area Cost in Hard Real-Time Reconfigurable Systems

This article presents a methodology to build real-time reconfigurable systems that ensure that all the temporal constraints of a set of applications are met, while optimizing the utilization of the available reconfigurable resources. Starting from a static platform that meets all the real-time deadlines, our approach takes advantage of run-time reconfiguration in order to reduce the area needed while guaranteeing that all the deadlines are still met. This goal is achieved by identifying which tasks must be always ready for execution in order to meet the deadlines, and by means of a methodology that also allows reducing the area requirements.

Real-time load-side control of electric power systems

Two trends are emerging from modern electric power systems: the growth of renewable (e.g., solar and wind) generation, and the integration of information technologies and advanced power electronics. The former introduces large, rapid, and random fluctuations in power supply, demand, frequency, and voltage, which become a major challenge for real-time operation of power systems. The latter creates a tremendous number of controllable intelligent endpoints such as smart buildings and appliances, electric vehicles, energy storage devices, and power electronic devices that can sense, compute, communicate, and actuate. Most of these endpoints are distributed on the load side of power systems, in contrast to traditional control resources such as centralized bulk generators. This thesis focuses on controlling power systems in real time, using these load side resources. Specifically, it studies two problems.

(1) Distributed load-side frequency control: We establish a mathematical framework to design distributed frequency control algorithms for flexible electric loads. In this framework, we formulate a category of optimization problems, called optimal load control (OLC), to incorporate the goals of frequency control, such as balancing power supply and demand, restoring frequency to its nominal value, restoring inter-area power flows, etc., in a way that minimizes total disutility for the loads to participate in frequency control by deviating from their nominal power usage. By exploiting distributed algorithms to solve OLC and analyzing convergence of these algorithms, we design distributed load-side controllers and prove stability of closed-loop power systems governed by these controllers. This general framework is adapted and applied to different types of power systems described by different models, or to achieve different levels of control goals under different operation scenarios. We first consider a dynamically coherent power system which can be equivalently modeled with a single synchronous machine. We then extend our framework to a multi-machine power network, where we consider primary and secondary frequency controls, linear and nonlinear power flow models, and the interactions between generator dynamics and load control.

(2) Two-timescale voltage control: The voltage of a power distribution system must be maintained closely around its nominal value in real time, even in the presence of highly volatile power supply or demand. For this purpose, we jointly control two types of reactive power sources: a capacitor operating at a slow timescale, and a power electronic device, such as a smart inverter or a D-STATCOM, operating at a fast timescale. Their control actions are solved from optimal power flow problems at two timescales. Specifically, the slow-timescale problem is a chance-constrained optimization, which minimizes power loss and regulates the voltage at the current time instant while limiting the probability of future voltage violations due to stochastic changes in power supply or demand. This control framework forms the basis of an optimal sizing problem, which determines the installation capacities of the control devices by minimizing the sum of power loss and capital cost. We develop computationally efficient heuristics to solve the optimal sizing problem and implement real-time control. Numerical experiments show that the proposed sizing and control schemes significantly improve the reliability of voltage control with a moderate increase in cost.

Real-Time Voltage Regulation in Power Distribution System Using Fuzzy Control

Two different fuzzy approaches to voltage control in electric power distribution systems are introduced in this paper. The real-time controller in each case would act on power transformers equipped with under-load tap changers. Learning systems are employed to turn the voltage-control relays into adaptive devices. The scope of this study has been limited to the power distribution substation, and the voltage measurements and control actions are carried out on the secondary bus. The capacity of fuzzy systems to handle approximate data, together with their unique ability to interpret qualitative information, make it possible to design voltage-control strategies that satisfy the requirements of the Brazilian regulatory bodies and the real concerns of the electric power distribution companies. Fuzzy control systems based on these two strategies have been implemented and the test results were highly satisfactory.

Robust integration of real time optimization with linear model predictive control

Here, we study the stable integration of real time optimization (RTO) with model predictive control (MPC) in a three layer structure. The intermediate layer is a quadratic programming whose objective is to compute reachable targets to the MPC layer that lie at the minimum distance to the optimum set points that are produced by the RTO layer. The lower layer is an infinite horizon MPC with guaranteed stability with additional constraints that force the feasibility and convergence of the target calculation layer. It is also considered the case in which there is polytopic uncertainty in the steady state model considered in the target calculation. The dynamic part of the MPC model is also considered unknown but it is assumed to be represented by one of the models of a discrete set of models. The efficiency of the methods presented here is illustrated with the simulation of a low order system. (C) 2010 Elsevier Ltd. All rights reserved.

Structuring real-time Object-Z specifications

This paper presents a means of structuring specifications in real-time Object-Z: an integration of Object-Z with the timed refinement calculus. Incremental modification of classes using inheritance and composition of classes to form multi-component systems are examined. Two approaches to the latter are considered: using Object-Z's notion of object instantiation and introducing a parallel composition operator similar to those found in process algebras. The parallel composition operator approach is both more concise and allows more general modelling of concurrency. Its incorporation into the existing semantics of real-time Object-Z is presented.

An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.

Standard Values for Real-Time Transthoracic Three-Dimensional Echocardiographic Dyssynchrony Indexes in a Normal Population

Background: There is a paucity of information describing the real-time 3-dimensional echocardiography (RT3DE) and dyssynchrony indexes (DIs) of a normal population. We evaluate the RT3DE DIs in a population with normal electrocardiograms and 2- and 3-dimensional echocardiographic analyses. This information is relevant for cardiac resynchronization therapy. Methods: We evaluated 131 healthy volunteers (73 were male, aged 46 +/- 14 years) who were referred for routine echocardiography; who presented normal cardiac structure on electrocardiography, 2-dimensional echocardiography, and RT3DE; and who had no history of cardiac diseases. We analyzed 3-dimensional left ventricular ejection fraction, left ventricle end-diastolic volume, left ventricle end-systolic volume, and left ventricular systolic DI% (6-, 12-, and 16-segment models). RT3DE data were analyzed by quantifying the statistical distribution (mean, median, standard deviation [SD], relative SD, coefficient of skewness, coefficient of kurtosis, Kolmogorov-Smirnov test, D`Agostino-Pearson test, percentiles, and 95% confidence interval). Results: Left ventricular ejection fraction ranged from 50% to 80% (66.1% +/- 7.1%); left ventricle end-diastolic volume ranged from 39.8 to 145 mL (79.1 +/- 24.9 mL); left ventricle end-systolic volume ranged from 12.9 to 66 mL (27 +/- 12.1 mL); 6-segment DI% ranged from 0.20% to 3.80% (1.21% +/- 0.66%), median: 1.06, relative SD: 0.5482, coefficient of skewness: 1.2620 (P < .0001), coefficient of Kurtosis: 1.9956 (P = .0039); percentile 2.5%: 0.2900, percentile 97.5%: 2.8300; 12-segment DI% ranged from 0.22% to 4.01% (1.29% +/- 0.71%), median: 1.14, relative SD: 0.95, coefficient of skewness: 1.1089 (P < .0001), coefficient of Kurtosis: 1.6372 (P = .0100), percentile 2.5%: 0.2850, percentile 97.5%: 3.0700; and 16-segment DI% ranged from 0.29% to 4.88% (1.59 +/- 0.99), median: 1.39, relative SD: 0.56, coefficient of skewness: 1.0792 (P < .0001), coefficient of Kurtosis: 0.9248 (P = .07), percentile 2.5%: 0.3750, percentile 97.5%: 3.750. Conclusion: This study allows for the quantification of RT3DE DIs in normal subjects, providing a comparison for patients with heart failure who may be candidates for cardiac resynchronization therapy. (J Am Soc Echocardiogr 2008; 21: 1229-1235)

Value of real time three-dimensional echocardiography in patients with hypertrophic cardiomyopathy: Comparison with two-dimensional echocardiography and magnetic resonance imaging

Real time three-dimensional echocardiography (RT3DE) has been demonstrated to be an accurate technique to quantify left ventricular (LV) volumes and function in different patient populations. We sought to determine the value of RT3DE for evaluating patients with hypertrophic cardiomyopathy (HCM), in comparison with cardiac magnetic resonance imaging (MRI). Methods: We studied 20 consecutive patients with HCM who underwent two-dimensional echocardiography (2DE), RT3DE, and MRI. Parameters analyzed by echocardiography and MRI included: wall thickness, LV volumes, ejection fraction (LVEF), mass, geometric index, and dyssynchrony index. Statistical analysis was performed by Lin agreement coefficient, Pearson linear correlation and Bland-Altman model. Results: There was excellent agreement between 2DE and RT3DE (Rc = 0.92), 2DE and MRI (Rc = 0.85), and RT3DE and MRI (Rc = 0.90) for linear measurements. Agreement indexes for LV end-diastolic and end-systolic volumes were Rc = 0.91 and Rc = 0.91 between 2DE and RT3DE, Rc = 0.94 and Rc = 0.95 between RT3DE and MRI, and Rc = 0.89 and Rc = 0.88 between 2DE and MRI, respectively. Satisfactory agreement was observed between 2DE and RT3DE (Rc = 0.75), RT3DE and MRI (Rc = 0.83), and 2DE and MRI (Rc = 0.73) for determining LVEF, with a mild underestimation of LVEF by 2DE, and smaller variability between RT3DE and MRI. Regarding LV mass, excellent agreement was observed between RT3DE and MRI (Rc = 0.96), with bias of -6.3 g (limits of concordance = 42.22 to -54.73 g). Conclusion: In patients with HCM, RT3DE demonstrated superior performance than 2DE for the evaluation of myocardial hypertrophy, LV volumes, LVEF, and LV mass.

Qualitative and Quantitative Real Time Myocardial Contrast Echocardiography for Detecting Hibernating Myocardium

Background: Real time myocardial contrast echocardiography (RTMCE) is an emerging imaging modality for assessing myocardial perfusion that allows for noninvasive quantification of regional myocardial blood flow (MBF). Aim: We sought to assess the value of qualitative analysis of myocardial perfusion and quantitative assessment of myocardial blood flow (MBF) by RTMCE for predicting regional function recovery in patients with ischemic heart disease who underwent coronary artery bypass grafting (CABG). Methods: Twenty-four patients with coronary disease and left ventricular systolic dysfunction (ejection fraction < 45%) underwent RTMCE before and 3 months after CABG. RTMCE was performed using continuous intravenous infusion of commercially available contrast agent with low mechanical index power modulation imaging. Viability was defined by qualitative assessment of myocardial perfusion as homogenous opacification at rest in >= 2 segments of anterior or >= 1 segment of posterior territory. Viability by quantitative assessment of MBF was determined by receiver-operating characteristics curve analysis. Results: Regional function recovery was observed in 74% of territories considered viable by qualitative analysis of myocardial perfusion and 40% of nonviable (P = 0.03). Sensitivity, specificity, positive and negative predictive values of qualitative RTMCE for detecting regional function recovery were 74%, 60%, 77%, and 56%, respectively. Cutoff value of MBF for predicting regional function recovery was 1.76 (AUC = 0.77; 95% CI = 0.62-0.92). MBF obtained by RTMCE had sensitivity of 91%, specificity of 50%, positive predictive value of 75%, and negative predictive value of 78%. Conclusion: Qualitative and quantitative RTMCE provide good accuracy for predicting regional function recovery after CABG. Determination of MBF increases the sensitivity for detecting hibernating myocardium. (Echocardiography 2011;28:342-349).

Genetic associations between carcass traits measured by real-time ultrasound and scrotal circumference and growth traits in Nelore cattle

The aim of the present study was to evaluate the genetic correlations among real-time ultrasound carcass, BW, and scrotal circumference (SC) traits in Nelore cattle. Carcass traits, measured by real-time ultrasound of the live animal, were recorded from 2002 to 2004 on 10 farms across 6 Brazilian states on 2,590 males and females ranging in age from 450 to 599 d. Ultrasound records of LM area (LMA) and backfat thickness (BF) were obtained from cross-sectional images between the 12th and 13th ribs, and rump fat thickness (RF) was measured between the hook and pin bones over the junction between gluteus medius and biceps femoris muscles. Also, BW (n = 22,778) and SC ( n = 5,695) were recorded on animals born between 1998 and 2003. The BW traits were 120, 210, 365, 450, and 550-d standardized BW (W120, W210, W365, W450, and W550), plus BW (WS) and hip height (HH) on the ultrasound scanning date. The SC traits were 365-, 450-, and 550-d standardized SC (SC365, SC450, and SC550). For the BW and SC traits, the database used was from the Nelore Breeding Program-Nelore Brazil. The genetic parameters were estimated with multivariate animal models and REML. Estimated genetic correlations between LMA and other traits were 0.06 (BF), -0.04 ( RF), 0.05 (HH), 0.58 (WS), 0.53 (W120), 0.62 (W210), 0.67 (W365), 0.64 ( W450 and W550), 0.28 (SC365), 0.24 (SC450), and 0.00 ( SC550). Estimated genetic correlations between BF and with other traits were 0.74 ( RF), -0.32 (HH), 0.19 (WS), -0.03 (W120), -0.10 (W210), 0.04 (W365), 0.01 (W450), 0.06 ( W550), 0.17 (SC365 and SC450), and -0.19 (SC550). Estimated genetic correlations between RF and other traits were -0.41 (HH), -0.09 (WS), -0.13 ( W120), -0.09 ( W210), -0.01 ( W365), 0.02 (W450), 0.03 (W550), 0.05 ( SC365), 0.11 ( SC450), and -0.18 (SC550). These estimates indicate that selection for carcass traits measured by real-time ultrasound should not cause antagonism in the genetic improvement of SC and BW traits. Also, selection to increase HH might decrease subcutaneous fat as correlated response. Therefore, to obtain animals suited to specific tropical production systems, carcass, BW, and SC traits should be considered in selection programs.

A real time pricing approach to deal with excessive wind power situations

The introduction of wind power generation in several countries around the world, including in European countries, where energy policy directives have encouraged the use of renewables, led to several changes in market and power systems operation. The intensive integration of these sources has led to situations in which the demand is lower than the available renewable resources. In these situations a part of the available generation is wasted if not used for storage or to supply additional demand. This paper proposes a real time demand response methodology based on changing the electricity price for the consumers expecting an increase in the demand in the periods in which that demand is lower than the available renewable generation. The consumers response to the changes in electricity price is characterized by their price elasticity of demand considered distinct for each consumer type. The proposed methodology is applied to the Portuguese power system, in the context of the Iberian electricity market (MIBEL). The renewable-based producers are considered as special producers, with special tariffs, and so it is important to use the energy available as it will be paid anyway. In this context, consumers are entities actively participating in the operation of the market.

Real-time energy resources scheduling considering intensive wind penetration

The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Virtual power players dealing with excessive wind power situations using real time pricing

The increasing importance given by environmental policies to the dissemination and use of wind power has led to its fast and large integration in power systems. In most cases, this integration has been done in an intensive way, causing several impacts and challenges in current and future power systems operation and planning. One of these challenges is dealing with the system conditions in which the available wind power is higher than the system demand. This is one of the possible applications of demand response, which is a very promising resource in the context of competitive environments that integrates even more amounts of distributed energy resources, as well as new players. The methodology proposed aims the maximization of the social welfare in a smart grid operated by a virtual power player that manages the available energy resources. When facing excessive wind power generation availability, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. The proposed method is especially useful when actual and day-ahead wind forecast differ significantly. The proposed method has been computationally implemented in GAMS optimization tool and its application is illustrated in this paper using a real 937-bus distribution network with 20310 consumers and 548 distributed generators, some of them with must take contracts.

LMP triggered real time demand response events

Recent changes in power systems mainly due to the substantial increase of distributed generation and to the operation in competitive environments has created new challenges to operation and planning. In this context, Virtual Power Players (VPP) can aggregate a diversity of players, namely generators and consumers, and a diversity of energy resources, including electricity generation based on several technologies, storage and demand response. Demand response market implementation has been done in recent years. Several implementation models have been considered. An important characteristic of a demand response program is the trigger criterion. A program for which the event trigger depends on the Locational Marginal Price (LMP) used by the New England Independent System operator (ISO-NE) inspired the present paper. This paper proposes a methodology to support VPP demand response programs management. The proposed method has been computationally implemented and its application is illustrated using a 32 bus network with intensive use of distributed generation. Results concerning the evaluation of the impact of using demand response events are also presented.